Michigan vs. Louisville

With just over an hour left until the final college basketball game of the 2013 season, I give you one last look at Michigan and Louisville. Michigan comes in with the number one ranked offense in the country, Louisville comes in with the number one ranked defense in the country. Obviously the reason Louisville is favored is their "weakness" (offense) is better than Michigan's "weakness" (defense). Weakness is in quotes, because this is relatively speaking. It's difficult for a team to make it this far with a truly big weakness on either offense or defense.

John Gasaway explained how Louisville's offense has been really good in the tournament to date. I took a look at how both teams have done game by game this season on their weaker side of the ball. Tournament games are in blue:

Louisville's offensive performances in their five NCAA tournament games have been some of their best of the year. Michigan struggled some on defense against Kansas and they will need to be great tonight in order to cut down the nets.

Enjoy the show!

Keys for Wichita State

Earlier this week I wrote about what I call opponent "compatibility". I basically wanted to know if there was any evidence for bad matchups beyond simply the general strength of the two teams. Now, I decided to use that same sample to take a look at the Louisville-Wichita St game today. My sample includes every game from the 2009, 2010, 2011, and 2012 season. It also has 2013 games from up until the first week of March.

I started my analysis by looking at defenses over the five years that force turnovers between 26 and 29 percent of possessions. Louisville is right in the middle of these teams at 27.5%. I identified 508 games where there was a defense with this high of a forced TO%. The following is a histogram of the TO% these defenses forced in the 508 games:

Obviously, 25%-29% is the most likely outcome. Overall, we have a very symmetrical distribution. The next step was to look at the result of game TO% on offensive efficiency. We would expect the lower TO% to be better for the offensive (higher points per possession), but it should be noted that there are correlations between the four factors themselves. In other words, a good TO% is more likely to be good at shooting, rebounding, and getting to the line than a bad TO% team. With that in mind, here's how offenses fared against pressure defenses:

The final step for this post was to look at the best offensive performances against high turnover defenses. Basically a visual look at how teams in Wichita State's position tonight have been successful:

In every single case, the offense shot the ball at a high percentage. There has been a lot of focus on if Wichita State can take care of the ball against the Louisville pressure. However, the recipe for success for teams in the Shockers' position has been to get hot from the floor and keep the TO% on a manageable (low to mid 20s) level. Easier said than done against Louisville.

The Highs and Lows of LaQuinton Ross' Weekend

LaQuinton Ross sent Ohio State to the Elite Eight with a three pointer against Arizona. Just type his name into Google and you can pick from tons of articles that tell you that. However, Ross was involved in an equally as crucial three pointer that played a tremendous role in sending Wichita State to the Final Four. Ross' shot may have gotten the attention of the media, but his defense went virtually unnoticed (to my knowledge).

With 2:30 left in the game, Ohio State had nearly completed their comeback. Wichita State was up three and had the ball. Ohio State was really one stop away from getting in great position to win the game. Wichita State broke the pressure and with 17 seconds left on the shot clock had the ball pulled out:

In the photo above, you can see the start to Wichita State's high pick and roll. Ross is circled and at this point is in reasonable guarding position on Tekele Cotton considering the context of the play.

Continuing on with the play, off of the pick and roll Ross does the right thing by sinking into the lane. It looks like he had the defensive assignment of showing on the roll man. His job is to be in a position where he can make the pass to the roller difficult while also being able to close out on his actual man. At this point in the play (above), Ross is in position to do just that.

The pick and roll ultimately proves unsuccessful for Wichita State. Ohio State switched the screen and Deshaun Thomas winds up guarding Fred Van Vleet (the ball handler). It appears that Wichita State is content with simply spreading the floor and letting Van Vleet create as the shot clock winds down. However, before Van Vleet looks to make his move, this happens:

Maybe somebody reading this can shed light on what exactly Ross is doing in the GIF above. The pick and roll is over, so he should be closer to the passing lane between Van Vleet and Cotton. He points at a screen occurring behind him and then right after points at his man (Cotton). I think he just got mentally lost on the floor and pointed at Cotton only to realize at the last second that was his man.

The point here is not that Ross is a bad defender. Obviously this one play does not define Ross as a defender or as a player in general. The real point is the focus on offense over defense. In my opinion, Ross' defensive blunder was just as important as his offensive heroics. However, the two plays were not treated close to equally in the analysis of Ohio State's weekend performance.

Davante Gardner: Zone Buster

Syracuse's 2-3 zone last night looked invincible versus the number one offense in the country. Indiana had scored more points per possession than their opponents (on average) give up in every game this season until Temple and Syracuse. Syracuse's defensive dominance had people wondering why a team would play anything other than zone. I went back and looked at Syracuse's defensive performances throughout the season. Sure enough, their worst of the year (allowing 1.21 points per possession) came to none other than Marquette.

It seems like a no-brainer to zone Marquette. Buzz Williams' squad is having one of the best offensive seasons ever for a team that shoots the three ball so poorly. Marquette ranks 19th in offensive efficiency in the nation despite shooting just 30.5% from three on the season. In theory, a 2-3 zone forces an offense to make deep shots. Marquette doesn't have the personnel to consistently knock down threes, but they do have Davante Gardner. Gardner is one of the most unique big men in the country. He is listed at 290 pounds, shoots 84.4% from the foul line, and can euro step. He also just happened to have his best performance of the season against the Orange in February.

Gardner went a perfect 7-7 from the field and went 12-13 from the foul line against Cuse the first time around. He also had just one turnover and four offensive rebounds. Gardner is a zone killer in the paint. His big body and nice touch disrupt what the Orange try to do defensively. First, let's look at the most obvious impact Gardner has against the zone: Occupying space.

In the photo above Gardner seals his man and clears out the lane. The result of this play was actually a basket for Jamil Wilson (the other guy posting up down low). Gardner constantly makes contact with the zone, clearing space in the process for others to work.

The following is a look at the three ways Davante Gardner is a zone buster:

1. Inside Finishing

If you want to know about Syracuse's shot blocking abilities, just ask Cody Zeller. Last night nothing came easy for Zeller and Indiana. However, Gardner is effective in a much different manner. He doesn't rely on athleticism as much as strength and a great touch. When Gardner got the ball down low against the zone, he used his body to prevent being blocked and to get to the foul line.

2. Offensive Rebounding

The zone is notoriously susceptible to second chance opportunities. Gardner is 89th in the country in offensive rebounding percentage. In the first meeting, he got four offensive rebounds from his positioning and strength. Maybe the most important aspect of his offensive rebounds is the ensuing put back. Gardner was able to clear space and get easy baskets down low off Marquette misses.

3. Foul Line Jumper

In the high post, Gardner forces Syracuse to respect his foul line jump shot. I found four plays where Gardner's ability to either force the zone extend or knock down a jump shot led to Marquette points. The first play the zone extends and Gardner hits the open man down low. The second play Gardner starts at the high post and cuts down the lane during a baseline drive for an easy lay-up. Finally, the last two plays Syracuse doesn't get out far enough and Gardner hits both a floater and a jumper.

Marquette doesn't need a great three point shooting performance to advance to the Final Four. In the first meeting, Marquette shot just 5-21 from three and yet still posted the best points per possession total of any Syracuse opponent this season. Gardner is the straw the stirs the drink against the zone for the Golden Eagles.

Indiana's Weakness

If you were to force me to pick a team I think is going to win it all, I would likely take Indiana. On the Sweet 16 efficiency graph, the Hoosiers have the best offense of anyone and an average defense (relative to the other 15 teams). C.J. Moore pointed out recently that the Hoosiers' weakness is playing at a slow pace. Moore noted that Indiana's record is bad in games with 64 possessions or less.

I am naturally pretty skeptical of change in pace being a big factor in a team's success. Ty Lawson's UNC team from a while back is the prime example. They played at a tremendous pace, but were equally as deadly in the half court (contrary to popular opinion). Great teams tend to be great, pretty much regardless of pace. To examine Indiana, I wanted to go beyond simply looking at their record by pace. Instead, I looked at the effect of pace on offensive efficiency and defensive efficiency. I wanted to make sure to account for strength of schedule. To do this I calculated AdjO and AdjD for each game as:

AdjO = (Indiana's Game Points Per 100 Possessions) - (Opponent's Average AdjD)

AdjD = (Opponent's Average AdjO) - (Indiana Opponent's Game Points Per 100 Possessions)
Note: Higher numbers are a good thing for Indiana for BOTH AdjO and AdjD

The highlighted portion of the table shows the culprit of Indiana's struggles. In games with under 65 possessions, the Hoosiers are fine offensively but have been much worse defensively. This is probably an unexpected finding, but I think there are some reasonable explanations. First, I didn't think for a second that Indiana would be a worse offensive team in slow paced games. The Hoosiers have the number one offense in the country. The number one offense in the country isn't likely to have any big weakness. Regardless of the pace of game, Indiana can score the basketball. Still, the question remains: why does Indiana's defense struggle in slow paced games? 

The convenient answer is to blame it on Jordan Hulls. He has been perceived as Indiana's defensive weakness for most of the season. This very well might be a part of it. In the half court, opponents may be able to expose Hulls as an on ball defender. Maybe a better reason is Indiana's defensive style. The Hoosiers  don't let their opponents get good looks and don't foul. They are 18th in the country in opponent eFG% and 14th in the country in opponent FTRate. However, they are very average when it comes to rebounding (152 in DR%) and turning teams over (120 in TO%). I suspect that these defensive shortcomings are more exposed in a grind it out, slow paced game.

The following shows the effects of pace on Indiana in graphical form: 

As you can see, Indiana's round of 32 game was an exception to their season performance. Indiana was very good defensively on Sunday, but scored fewer points per possession than their opponent's defensive average for the first time all season. The thing that might stand out most to me from these graphs is Indiana's defense against faster paced teams. In games over 70 possessions, Indiana's defense has been great. Like I said before, IU's offense is great regardless of pace. So in uptempo games, it's going to be very difficult to beat the Hoosiers.

Visualizing the Sweet 16

The following is a visualization of the teams and top players remaining in the Sweet 16. All statistics are full season averages (the last two games included):

1. Adjusted efficiency of remaining teams per kenpom.com

2. Adjusted tempo of remaining teams per kenpom.com

3. The offensive and defensive four factors of all 16 teams. These are NOT schedule adjusted. (Click to enlarge)

4. The top players remaining by efficiency and by usage/volume. Note: numbers are not adjusted for schedule

Final Four Values

The running narrative for the NCAA this season has been all about the parity at the top. Yet here we are in mid March and despite "the field being wide open", everyone is taking Louisville. Now I'm not saying this is a bad idea. Louisville may end up cutting down the nets in Atlanta. However, by picking Louisville you are forcing yourself to have a "near" perfect bracket in order to win your pool. In a standard scoring system, you generally have to get the national champion right to win it all (with an example of an exception being if Butler had won). If you are one of the few people in your pool to take a unique team to win it all, you don't have to be all that great with your earlier picks. With Louisville, however, you're going to have to somehow pick up points on other people with Louisville.

On ESPN, you can currently look at the percentage of people in the country taking any team to reach any round. I thought it would be interesting to compare the average person's picks to Ken Pomeroy's log 5 projections. This will help determining the "value" of final four picks. If a team's value is especially high, it might be worth it to take the gamble in order to attempt to position yourself better among other Louisville brackets. Obviously the log 5 projections aren't perfect. Thus, I decided to include the Vegas odds that each team reaches the final four in the table too. The Vegas odds weren't actually used in finding value teams, but they can either reinforce (or not) the log 5 rankings.

The DIFF column on the right is simply (log 5 final four%) - (ESPN final four%). The thing that jumps out is the "Florida Effect". Not only does Florida shatter the top spot for best value, but they also turn Georgetown and Kansas into bad values. There's a whole bunch of uncertainty surrounding the Gators, but if you trust log 5 (and Vegas) they are nearly a must in your bracket. Miami and Ohio State are the other two that stand out. The conference tournaments have a ridiculous amount of pull on ESPN brackets, or so it seems. Ohio State, Miami, Kansas, and Louisville are all in the top five most picked final four teams (with Indiana) and are coming off conference tournament championships. Syracuse has struggled, but they seem like a much better alternative to Indiana in the East than Miami. Finally, if you decide to go with Pitt in your final four, log 5 says you have an 11.7% chance of taking a commanding lead in your pool.

Finding an Upset: Three Pointers

Every year in the NCAA tournament, inferior team beat superior teams. Norfolk State was not a better team than Missouri, they just scored more points over a 40 minute period. The cause behind these upsets is variability. It's no shocking revelation that three point shots increase variability. The three point shot has long been known as a great equalizer.

Underdogs need to increase variability by taking riskier strategies (i.e. shooting three pointers). If each team plays at their average, the favorite will win. Threes do NOT ensure an underdog will play better, but if you're going to go out you might as well go out swinging.

To determine which tournament matchups should have the most variability from a three point shooting perspective, I looked at the percentage of three point attempts taken and allowed for both teams (the favorite and the underdog). 3PA% is different from 3P%. I am not concerned with how often a team makes threes. In one single game that number will be difficult to predict. 3PA%, on the other hand, identifies just how often threes are attempted.

Key Takeaways

New Mexico and Florida each rely the most heavily on threes of all the favorites. However, they were fortunate enough to draw opponents that don't rely on them. Florida got one of the most unique teams in the country in Northwestern State. Which leads me to my next point...

Northwestern State is an interesting basketball team. Not only do they play at the fastest pace of any team in the country, but they also don't rely on the three at all. They don't take many and they don't let their opponents take many either.

Miami and Georgetown may be the "best" bets at becoming this year's Duke and Missouri. That would make Pacific and Florida Gulf Coast this year's Norfolk St. and Lehigh. I put best in quotes, because obviously all the games we are dealing with in this analysis are long shots. However, the numbers say that Miami and Georgetown are still relatively more likely to have an off night than others top teams.

Valpo and Davidson may want to consider changing up their defenses. Marquette and Michigan State rarely take threes on the offensive end. Coincidentally, Valpo and Davidson rarely allow threes on the defensive end. However, both Marquette and MSU shoot over 50% from two. If the two underdogs want a better shot at reaching the round of 32, changing their normally great defensive strategy might be a good idea.

The Selection Committee's Tendencies

Tomorrow is selection Sunday, the day bracketology ceases to matter. Personally, I have never really been into dissecting resumes for the bubble teams. Still, I decided to take a look at some of the committee's tendencies between 2006-2012. I think this information is probably more interesting than insightful, as the committee's decisions have a human element to them that are constantly changing.

First, I went to bracketmatrix.com to determine the bubble teams from the past seven years. Bracket Matrix compiles the bracketology of all sites on the internet into one. I decided that if a team was picked in the field on more than 5% of all brackets but less than 95% of all brackets, then they were a bubble team. There were a few exceptions to the rule, but I think it was good enough. 72 teams fit this criteria over the seven years of data.

The first thing I wanted to do was look at the committee's reliance on RPI. I took the average RPI of bubble teams that received bids and the average RPI of bubble teams that did NOT receive bids for each year:

The graph shows that in recent years, the difference in the RPIs of the teams in and out have been very significant. This is a tricky graph to interpret and I don't necessarily think the committee has become more reliant on RPI (as the graph seems to indicate). In 2006 and 2007, teams from conferences like the Missouri Valley had figured out the RPI formula. They were scheduling games to maximize their RPI and naturally not all of them could get in. Still, the graph is a bit concerning for proponents of a reality based selection process.

Next I wanted to look at the biggest surprises according to bracketologists. Basically, which teams have bracketologist been the most wrong on throughout the year?

2006 appears to be the worst year in bracketology history. Only one of 23 people had Air Force and Utah State in the field and yet both got in. In recent years many sites are now doing bracketology, and I believe there has been an increase in both quantity and quality. I wasn't surprised to see a Seth Greenberg Virginia Tech team in the biggest snubs. 87 of 89 bracketologists had the Hokies in the tournament in 2011 despite an RPI of 62.

Next, let's look at the biggest surprises based on RPI:

Notice the conference RPIs for these teams. The snubs were almost all in weaker conferences than the most surprising bids. USC was the worst team according to RPI to get a bid in 2011. All of the RPI snubs are from 2006-2008. This makes sense based on the results of the first graph.

I can't wait for the bubble discussion to end and the actual NCAA tournament analysis to begin. However, I haven't seen much research done on the recent history of the selection committee and thought this could shed some light on that.